2026-10-06T13:40:31Z https://www.scidb.cn/oai

10.57760/sciencedb.j00273.0002q 2026-09-30T11:07:27Z

2026-09-30 The data of "Stiffness tensor-guided intelligent design and performance validation of two-dimensional mechanical functional materials " doi:10.57760/sciencedb.j00273.0002q en This dataset is accompanied by 14 statistical data tables and 4 representative crystal structure files, supporting research conclusions from training set distribution, conditional encoding mechanism, generation quality, to first principles verification. Figure 2 shows the stiffness distribution, spatial group composition, and Young's modulus classification of 8454 materials in the C2DB training set. Figure 3 shows the difference in stiffness distribution between unconditional baseline and conditional guidance. Figure 4 shows the stability/uniqueness/novelty of 8 sets of conditions. Figure 5 summarizes the validation results of 80 structural VASP DFT elastic constants, and lists the target values, calculated values, and Pearson correlation coefficients in a unified manner, visually demonstrating the quantitative correspondence between target stiffness and DFT values. Figure 7 quantitatively demonstrates the independent adjustability of single component through three sets of C22/C66/C12 independent control experiments and anisotropy verification. Four CIF files are selected to cover typical cases spanning the P10 to P95 stiffness quantiles, covering the stiffness range of 15-527 N/m, corresponding to the full functional application scenarios of flexible substrates, transition metal selenides, high stiffness nitrides, and superhard oxide coatings, providing visual structural examples for condition guided effects. The data file system presents the control ability of the stiffness tensor condition guided crystal generation method, providing data reference for tensor property driven material reverse design.  diffusion model; stiffness tensor; two-dimensional material; crystal structure generation Tong Boyuan Tingting Chen Liu Huang Ran Nian Song Erhong Liu Jianjun RESTRICTED dataset Science Data Bank